Map updating method and device, equipment, storage medium and program product

By statistically analyzing the popularity of road perception elements of crowdsourced vehicles, the problems of high cost and low accuracy in updating traditional electronic maps have been solved, achieving low-cost and efficient electronic map updates that meet the real-time requirements of autonomous driving.

CN122130107APending Publication Date: 2026-06-02合肥四维图新科技有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
合肥四维图新科技有限公司
Filing Date
2026-02-10
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Traditional electronic map updates rely on specialized equipment, which is costly and has a long update cycle. This cannot meet the real-time map requirements of autonomous driving. Furthermore, existing crowdsourced data has low accuracy, high noise, and poor consistency, leading to false positives and false negatives that affect the accuracy of updates.

Method used

By acquiring the driving trajectories and road perception elements reported by crowdsourced vehicles, a matching relationship between road perception elements and map elements is established, element popularity is calculated, and map updates are performed based on popularity. An element popularity management approach is adopted to improve the accuracy and timeliness of updates.

Benefits of technology

It achieves low-cost, efficient and accurate electronic map updates, making the maps closer to real-time road conditions, meeting the real-time map requirements of autonomous driving, and providing reliable navigation and geographic information services.

✦ Generated by Eureka AI based on patent content.

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Abstract

This application provides a map updating method, apparatus, device, storage medium, and program product. The method includes: acquiring driving trajectories reported by crowdsourced vehicles and the corresponding road perception elements; determining the map structure to be updated based on the driving trajectories, and determining the matching relationship between the road perception elements and map elements in the map structure to be updated; based on the matching relationship, statistically determining the element heat corresponding to the road perception elements and map elements respectively; and performing crowdsourced updating of the map structure to be updated based on the element heat and road perception elements. This application updates electronic maps through crowdsourced map updating technology, enabling low-cost, fast, and accurate updates to obtain electronic maps reflecting the latest state of real-world roads, meeting the real-time map requirements of autonomous driving.
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